^{Covid19 spread}

^{Data Assimilating real images in Sneezing And Coughing Simulations for realistic predictions}

for info please contact Dr Rossella Arcucci: r.arcucci@imperial.ac.uk

DSI-DataLearning and ESE-AMCG groups

working together for COVID19 spread predictions

The Data Science Institute, founded in 2014 by Professor Yi-Ke Guo, is one of the six Global Institutes of Imperial College London. It represents a hub for researchers and academics using data science tools in their research, be it in medicine, finance, engineering of natural sciences.

The Data Science Institute collaborates with the Department of Earth Science and Engineering for the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) in UK.

In particular, the DataLearning working group, lead by Dr Rossella Arcucci is working with the Applied Modelling and Computation Group (AMCG), lead by Professor Christopher Pain to improve sneezing and coughing simulations, assimilating real data from images in fluid-dynamic symulations. Prof Pain lead with Prof Linden (Cambridge) the RAMP Royal Society response to the COVID 19 risk associated with air flows and aerosols.

In the image:

The Data Assimilation model we apply here is the one described in the paper: "Arcucci, Rossella, et al. "Optimal reduced space for variational data assimilation." Journal of Computational Physics 379 (2019): 51-69. "
data from sneezing and coughing simulations have been provided by Dr Asiri Obeysekara (ESE, ICL)
observed data have been pre-processed by Dr Cesar Quilodran Casas (DSI, ICL).

How it works in a real world environment such as a School:

what is this parameter alpha? ...

... details about this application, the algorithm and the software are provided in a paper which will be online very soon.

Check this page to find a link to the paper as soon as the paper will be online in the next few days.

Sneezing

real image from Scharfman, B. E., et al. "Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets." Experiments in Fluids 57.2 (2016): 24.

^Coughing

real image from Scharfman, B. E., et al. "Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets." Experiments in Fluids 57.2 (2016): 24.

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